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January 17, 2020 05:26
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#Training of LDA topic models on bi-grams for each of the subsets | |
lda_model_bigrams_q1 = gensim.models.LdaMulticore(bi_corpus_q1, num_topics=10, id2word=dictionary_bi_q1, passes=2, workers=10) | |
lda_model_bigrams_q2 = gensim.models.LdaMulticore(bi_corpus_q2, num_topics=10, id2word=dictionary_bi_q2, passes=2, workers=10) | |
lda_model_bigrams_q3 = gensim.models.LdaMulticore(bi_corpus_q3, num_topics=10, id2word=dictionary_bi_q3, passes=2, workers=10) | |
lda_model_bigrams_q4 = gensim.models.LdaMulticore(bi_corpus_q4, num_topics=10, id2word=dictionary_bi_q4, passes=2, workers=10) |
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